Senior Machine Learning Engineer - Marketplace Pricing

About the Role

Uber's Marketplace is at the heart of Uber's business and the Dynamic Supply Pricing (DSP) team develops the models, algorithms, signals, and large-scale distributed systems that power real-time driver pricing for billions of rides. We use machine learning, optimization, and algorithmic game theory to set driver prices that dynamically align customers' and partners' interests while maximizing the value created by the marketplace.

We are looking for experienced candidates with a passion for building large-scale systems that optimize multi-sided real-time marketplaces. In this role, you will lead the design, development, and productionization of advanced ML models and pricing algorithms, covering deep learning, causal modeling, and reinforcement learning. You will work with engineers, product managers, and scientists to set the team's technical direction and solve some of Uber's most challenging and most complex business problems in order to provide earnings opportunities for millions of drivers worldwide.

\\-\\-\\-\\- What You Will Do ----

- Lead the design, development, and productionization of end-to-end ML solutions for large-scale distributed systems serving billions of trips
- Develop novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
- Partner with the marketplace leadership team to set the team's technical direction and own its implementation, providing technical mentorship to junior engineers
- Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems

\\-\\-\\-\\- Basic Qualifications ----

- Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research
- 4+ years of experience in developing and deploying machine learning models and optimization algorithms in large-scale production environments
- Proficiency in programming languages such as Python, Scala, Java, or Go
- Experience with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
- Experience in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
- Deep understanding of machine learning algorithms and mathematical optimization (e.g. LP, convex optimization)

\\-\\-\\-\\- Preferred Qualifications ----

- Experience leading complex technical projects and influencing the scope and output of others
- Track record of translating ambiguous business problems into technical solutions and driving multi-functional projects
- Excellent communication skills to lead initiatives and collaborate effectively with cross-functional partners
- Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
- Experience in reinforcement learning and causal machine learning

For New York, NY-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.

For San Francisco, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.

For Seattle, WA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.

For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link [](;br>
Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](;br>
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.